Brendan McEwen

Bedbug Female Fitness

You are an evolutionary biologist studying sexual conflict and the effect of mating frequency on female lifetime fitness. Your study system is the notorious bedbug Climex lectularis.  Bedbugs live in mixed-sex aggregations where females are subject to frequent reproductive harassment from males. Due to this reproductive harassment, females vary in their mating rates in natural groups where some females mate relatively infrequently, and others mate much more frequently. Higher mating rates for females increase the number of offspring produced per unit time, but may impose a longevity penalty as the physical process of reproduction is costly. This trade-off begs the question of whether variation in mating rate leads to a change overall lifetime fitness (number of viable offspring produced). To answer this question, you subjected females to a high-frequency (High) or low-frequency (Low) mating frequency treatment (Treatment). You counted the number of total viable offspring each female produced in her lifetime (Hatchlings), as well as her total lifetime in days (Longevity). You recorded your results in the dataframe held in “femalefitness.csv”.

  1. Load the data. Create a new column called FemaleID, which contains a unique identifier label for each row. Rearrange the columns so that FemaleID is the left-most column of the dataframe.
  2. Produce two boxplots:
    • One in base r graphics, showing the variation in hatchlings produced by low-frequency mating females versus high-frequency mating females
    • One in ggplot, showing the variation in longevity of low-frequency mating females versus high-frequency mating females. Distinguish between treatments such that the low-frequency female box is light green, and the high frequency mating box is light blue
  3. Create separate histograms of hatchlings produced for the Low and High mating frequency treatment females. Adjust the x-axis limits so that the histograms are printed on the same scale
  4. Using the simplest possible statistical test that is appropriate for this scenario, test whether mating rate has an effect on female lifetime fitness. Verbally explain the null hypothesis, and give an inferential statement for your result.
  5. Using the simplest possible statistical test that is appropriate for this scenario, test whether mating rate has an effect on female longevity
  6. Compute the odds ratio between a female in the low mating frequency treatment living past 70 days versus a female in the High mating frequency treatment living past 70 days. Give a verbal explanation of what this actually ‘means’.

Files to download:

To download, right-click and press “Save File As” or “Download Linked File”

  1. femalefitness.csv

Laboratory and Institution or PI

Cognitive Ecology Lab, Dr. Reuven Dukas, McMaster University Department of Psychology, Neuroscience, & Behaviour https://psych.mcmaster.ca/dukas/index.htm 

References and Further Reading

Yan, J. L., & Dukas, R. (2022). The social consequences of sexual conflict in bed bugs: social networks and sexual attraction. Animal Behaviour192, 109-117.

Parker, G. A. (2006). Sexual conflict over mating and fertilization: an overview. Philosophical Transactions of the Royal Society B: Biological Sciences361(1466), 235-259.

Maklakov, A. A., Bilde, T., & Lubin, Y. (2005). Sexual conflict in the wild: elevated mating rate reduces female lifetime reproductive success. the american naturalist165(S5), S38-S45.

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